Hospital harm captured by this indicator is defined as the risk-adjusted rate of acute care hospitalizations with at least one occurrence of unintended harm during a hospital stay that could have been potentially prevented by implementing known evidence-informed practices. This includes many types of harm at a system level (making it a big dot indicator). It also classifies harm into actionable clinical groups; therefore, improvement efforts in patient safety can be tracked at the facility level overall and for each specific clinical group.

While not all instances of harm captured by this indicator can be prevented, adoption of evidence-informed practices can help to reduce the rate of harm.

Harm is captured only when it
–Is identified as having occurred after admission and within the same hospital stay;
–Requires treatment, alters treatment or prolongs the hospital stay; and
–Is one of the conditions from the 31 clinical groups in the Hospital Harm Framework (refer to the Hospital Harm Appendices).

The following are not captured:
–Near misses or incidents that did not reach the patient; and
–Reportable incidents or events that reached the patient and could potentially have caused harm or injury but did not.

Hospital harm captured by this indicator is defined as the risk-adjusted rate of acute care hospitalizations with at least one occurrence of unintended harm during a hospital stay that could have been potentially prevented by implementing known evidence-informed practices. This includes many types of harm at a system level (making it a big dot indicator). It also classifies harm into actionable clinical groups; therefore, improvement efforts in patient safety can be tracked at the facility level overall and for each specific clinical group.

While not all instances of harm captured by this indicator can be prevented, adoption of evidence-informed practices can help to reduce the rate of harm.

Harm is captured only when it
–Is identified as having occurred after admission and within the same hospital stay;
–Requires treatment, alters treatment or prolongs the hospital stay; and
–Is one of the conditions from the 31 clinical groups in the Hospital Harm Framework (refer to the Hospital Harm Appendices).

The following are not captured:
–Near misses or incidents that did not reach the patient; and
–Reportable incidents or events that reached the patient and could potentially have caused harm or injury but did not.

4 logistic regression models built separately for obstetric, pediatric, surgical and medical patient groups are used to calculate the results. Coefficients derived from these 4 logistic regression models are used to calculate the probability of identifying hospital harm for each case. The expected number of hospital discharges with harm is the sum of these probabilities in that hospital. The risk-adjusted Hospital Harm rate is calculated by dividing the observed number of discharges with a hospital harm event in each hospital by the expected number of discharges with hospital harm and multiplying by the Canadian average Hospital Harm rate.

This indicator is expressed as the number of hospital discharges with at least one occurrence of harm per 100 discharges.

Unit of analysis: Hospital discharge

Calculation: Geographic Assignment

Place of service

Calculation: Type of Measurement

Rate - Rate — per 100

Calculation: Adjustment Applied

The following covariates are used in risk adjustment:
The 4 patient groups are hierarchically defined in the following order and are used to build models, adjusting for the covariates listed below:

1. Obstetric patient group
Age, malposition/malpresentation of fetus, gestational age, large fetus and transfer from a health care institution

5. Discharges with selected mental health diagnoses (i.e., most responsible diagnosis ICD-10-CA codes F10–F99). In Ontario, mental health discharges are submitted to the Ontario Mental Health Reporting System (OMHRS) and are therefore not in the Discharge Abstract Database (DAD). In order to create a standard hospital population, discharges with mental health disorders (with the exception of organic mental health disorders — ICD-10-CA codes F00–F09) were excluded from all provinces.

Numerator

Description:
A subset of the denominator: discharges with at least one occurrence of harm identified during the hospital stay Inclusions:
Harm is identified based on the International Statistical Classification of Diseases and Related Health Problems (ICD 10-CA)/Canadian Classification of Health Interventions (CCI) and the Canadian Coding Standards and is classified into 31 clinical groups under 4 categories of harm.

For detailed descriptions of the inclusions for clinical groups and categories of harm, please refer to the Hospital Harm Appendices.Exclusions:
For detailed descriptions of the exclusions for clinical groups and categories of harm, please refer to the Hospital Harm Appendices.

Patients expect hospital care to be safe, and for most people it is. Despite health professionals’ focus on safety, a small proportion of patients experience some type of unintended harm as a result of the care they receive. Concern over patient safety and how patients can be harmed during their hospital stay has grown steadily over the past decade.

Tracking and reporting harmful events is a vital first step to investigating, monitoring and understanding patient safety improvement efforts. Historically, reporting has been mostly voluntary and focused on particular risks such as infections. Until now, there has been no single measure that provides a broad perspective on patient safety in Canadian hospitals or answers the question “how safe is my hospital?”

This indicator aims to provide a single estimate of the overall risk-adjusted rate of hospital harm to allow for comparisons, tracking and monitoring over time at the facility, regional and provincial/territorial levels.

The Hospital Harm indicator has the following limitations that may affect interpretation of results and comparison across jurisdictions:

–The overall Hospital Harm rate is subject to coding bias, so hospitals with better documentation may have higher rates.
–Coding variation or coding culture differences may result in either under-reporting or over-reporting of certain occurrences of harm.
–Hospitals that have more patients with more complex conditions may not be fully risk adjusted.
–All occurrences of harm are considered to be of the same weight in terms of contribution to a hospital’s overall rate, regardless of severity.

Trending Issues

The Hospital Harm measure was released privately in February 2016 to allow hospitals to validate their results. In October 2016, CIHI released Measuring Patient Harm in Canadian Hospitals, a national-level report on hospital harm. Since the report was released, there have been changes to the methodology used. For detailed descriptions of the differences between those releases and the most recent one, please refer to the Hospital Harm Appendices.